Mindway AI, the Denmark-based responsible gambling technology provider, has brought on Will Mace to spearhead a new research initiative examining how gambling operators engage with their customers. The appointment signals a deeper push into evidence-based player protection, with Mace tasked specifically with studying the quality and effectiveness of operator-customer interactions. It arrives at a moment when regulators across multiple jurisdictions are tightening expectations around how licensees identify and respond to signs of gambling harm.
What Mace’s Appointment Means for the Responsible Gambling Sector
Before diving into the specifics, it is worth framing why this hire matters beyond a single company’s org chart. The gambling industry faces mounting pressure to demonstrate that customer interactions are not just box-ticking exercises but genuinely protective interventions. Mace’s research could shape how operators, regulators, and technology vendors measure the gap between policy and practice.
- Operator accountability under scrutiny: Regulators in the UK, across Europe, and in emerging US markets increasingly demand that licensees prove their customer interactions lead to measurable harm-reduction outcomes, not merely compliance on paper.
- Data-driven intervention models are replacing reactive approaches. Mace’s work at Mindway AI will likely feed into the company’s existing AI detection tools, refining how algorithms flag at-risk behaviour and how operators should respond.
- The appointment reinforces Mindway AI’s positioning as a research-first technology company rather than a pure software vendor.
- Talent movement: Mace’s decision to join a specialised AI firm rather than a major operator or consultancy suggests that the centre of gravity in responsible gambling innovation is shifting toward dedicated tech providers.
Who Is Will Mace?
Mace brings a research background focused on behavioural science and gambling-related harm. His previous work has centred on understanding the mechanisms through which gambling products create risk and how industry responses can be calibrated to reduce that risk without eliminating consumer choice entirely. That balance (a distinction regulators have been slow to codify in practice) sits at the heart of the debate Mindway AI is wading into.
At Mindway AI, Mace will lead a study specifically targeting the interactions that occur between operators and their customers during the player journey. This includes everything from initial affordability checks and deposit-limit conversations to the more sensitive interventions triggered when a player exhibits markers of harm. The question his research aims to answer is deceptively simple: do these interactions actually work?
Why Customer Interaction Quality Has Become a Regulatory Flashpoint
Across the UK, the Gambling Commission has issued multiple enforcement actions in recent years tied directly to failures in customer interaction. Operators have faced licence reviews and financial penalties not because they lacked policies, but because their execution fell short. The gap between written procedure and frontline delivery is where harm persists.
And while the UK remains the most visible enforcement environment, other jurisdictions are catching up. Sweden’s Spelinspektionen, the Netherlands’ Kansspelautoriteit, and several Australian state regulators have all moved toward requiring operators to document and justify their interaction strategies. The trend is unmistakable: regulators want evidence, not assurances.
This is precisely where Mindway AI’s responsible gambling technology platform fits. The company’s tools use neuroscience-based algorithms to detect patterns associated with problem gambling, but detection alone is only half the equation. What happens after a flag is raised depends on the operator’s interaction framework. Mace’s research targets that second half.
The Neuroscience of Player Behaviour and Operator Response
Understanding why certain customer interactions succeed while others fail requires more than compliance auditing. It demands a grasp of how players process information during periods of heightened emotional arousal, cognitive bias, and loss-chasing behaviour. Neurolinguistic framing plays a significant role here.
When an operator contacts a customer about their gambling patterns, the language used, the timing of the message, and the channel through which it arrives all influence whether the player engages constructively or dismisses the intervention. Research in behavioural psychology has shown that directive language (“you must reduce your spending”) tends to trigger reactance, a defensive psychological response that makes the player less likely to comply. Conversely, autonomy-supportive framing (“we’d like to help you review your options”) preserves the player’s sense of agency and increases the likelihood of a meaningful outcome.
Mace’s study could provide operators with empirically grounded frameworks for structuring these conversations. The implications extend beyond compliance. Operators that master the science of effective interaction stand to reduce regulatory risk, lower the social cost of gambling harm, and arguably build stronger long-term customer relationships. Still, whether the industry will adopt such findings uniformly remains an open question.
Timing matters too. A well-crafted message delivered at the wrong moment in a player’s session can be worse than no message at all. Interrupting a player mid-session with a generic pop-up, for instance, has been shown in multiple studies to produce negligible behavioural change. But a personalised follow-up sent during a cooling-off period, referencing specific patterns in the player’s recent activity, carries far more weight.
How This Fits Into Mindway AI’s Broader Strategy
Mindway AI has built its reputation on combining neuroscience research with machine learning to create tools that identify at-risk gambling behaviour in real time. The company’s GameScanner product, used by operators across Europe and North America, analyses player data to generate risk scores. Yet the company has acknowledged that detection without effective follow-through limits the impact of any technology solution.
Bringing Mace on board represents an investment in closing that loop. By studying what operators actually do once a risk is flagged, Mindway AI can refine not only its own product recommendations but also contribute to industry-wide standards for customer interaction. That dual purpose sets this research apart from purely commercial R&D.
Frequently Asked Questions
What will Will Mace’s research at Mindway AI focus on?
Mace will lead a study examining how gambling operators interact with customers, particularly during harm-prevention interventions. The goal is to assess whether current interaction practices produce meaningful outcomes or merely satisfy compliance requirements.
Why does customer interaction quality matter for gambling operators?
Regulators across multiple jurisdictions have shifted from evaluating whether operators have policies to evaluating whether those policies translate into effective action. Poor interaction quality has already led to enforcement actions and licence reviews in the UK and elsewhere. The financial and reputational stakes are significant.
How does Mindway AI’s technology relate to this research?
Mindway AI’s platform detects at-risk gambling behaviour using neuroscience-based algorithms. Mace’s research addresses what should happen after detection, giving operators evidence-based guidance on how to structure their responses. Together, detection and response form a more complete harm-prevention system.
